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• W3006663297 abstract "CVD is the leading cause of death worldwide, and genetic investigations into the human lipidome may provide insight into CVD risk. The aim of this study was to estimate the heritability of circulating lipid species and their genetic correlation with CVD traits. Targeted lipidomic profiling was performed on 4,492 participants from the Busselton Family Heart Study to quantify the major fatty acids of 596 lipid species from 33 classes. We estimated narrow-sense heritabilities of lipid species/classes and their genetic correlations with eight CVD traits: BMI, HDL-C, LDL-C, triglycerides, total cholesterol, waist-hip ratio, systolic blood pressure, and diastolic blood pressure. We report heritabilities and genetic correlations of new lipid species/subclasses, including acylcarnitine (AC), ubiquinone, sulfatide, and oxidized cholesteryl esters. Over 99% of lipid species were significantly heritable (h2: 0.06–0.50) and all lipid classes were significantly heritable (h2: 0.14–0.50). The monohexosylceramide and AC classes had the highest median heritabilities (h2 = 0.43). The largest genetic correlation was between clinical triglycerides and total diacylglycerol (rg = 0.88). We observed novel positive genetic correlations between clinical triglycerides and phosphatidylglycerol species (rg: 0.64–0.82), and HDL-C and alkenylphosphatidylcholine species (rg: 0.45–0.74). Overall, 51% of the 4,768 lipid species-CVD trait genetic correlations were statistically significant after correction for multiple comparisons. This is the largest lipidomic study to address the heritability of lipids and their genetic correlation with CVD traits. Future work includes identifying putative causal genetic variants for lipid species and CVD using genome-wide SNP and whole-genome sequencing data. CVD is the leading cause of death worldwide, and genetic investigations into the human lipidome may provide insight into CVD risk. The aim of this study was to estimate the heritability of circulating lipid species and their genetic correlation with CVD traits. Targeted lipidomic profiling was performed on 4,492 participants from the Busselton Family Heart Study to quantify the major fatty acids of 596 lipid species from 33 classes. We estimated narrow-sense heritabilities of lipid species/classes and their genetic correlations with eight CVD traits: BMI, HDL-C, LDL-C, triglycerides, total cholesterol, waist-hip ratio, systolic blood pressure, and diastolic blood pressure. We report heritabilities and genetic correlations of new lipid species/subclasses, including acylcarnitine (AC), ubiquinone, sulfatide, and oxidized cholesteryl esters. Over 99% of lipid species were significantly heritable (h2: 0.06–0.50) and all lipid classes were significantly heritable (h2: 0.14–0.50). The monohexosylceramide and AC classes had the highest median heritabilities (h2 = 0.43). The largest genetic correlation was between clinical triglycerides and total diacylglycerol (rg = 0.88). We observed novel positive genetic correlations between clinical triglycerides and phosphatidylglycerol species (rg: 0.64–0.82), and HDL-C and alkenylphosphatidylcholine species (rg: 0.45–0.74). Overall, 51% of the 4,768 lipid species-CVD trait genetic correlations were statistically significant after correction for multiple comparisons. This is the largest lipidomic study to address the heritability of lipids and their genetic correlation with CVD traits. Future work includes identifying putative causal genetic variants for lipid species and CVD using genome-wide SNP and whole-genome sequencing data. CVD is the leading cause of death globally, accounting for approximately 31% of all deaths in 2015 (1Roth G.A. Johnson C. Abajobir A. Abd-Allah F. Abera S.F. Abyu G. Ahmed M. Aksut B. Alam T. Alam K. et al.Global, regional, and national burden of cardiovascular diseases for 10 causes, 1990 to 2015.J. Am. Coll. Cardiol. 2017; 70: 1-25Crossref PubMed Scopus (1674) Google Scholar). Cardiometabolic traits associated with CVD include the standard lipid profile (“clinical lipids”), such as elevated LDL-C and triglycerides, and lowered HDL-C, and other factors such as elevated BMI, systolic blood pressure (SBP), and diastolic blood pressure (DBP) (2Ford E.S. Li C. Zhao G. Prevalence and correlates of metabolic syndrome based on a harmonious definition among adults in the US.J. Diabetes. 2010; 2: 180-193Crossref PubMed Scopus (313) Google Scholar). These traits are heritable, with the heritability of each trait dependent on the study type and sample used to measure heritability (3Elks C.E. den Hoed M. Zhao J.H. Sharp S.J. Wareham N.J. Loos R.J.F. Ong K.K. Variability in the heritability of body mass index: a systematic review and meta-regression.Front. Endocrinol. (Lausanne). 2012; 3: 29Crossref PubMed Scopus (322) Google Scholar). Typical reported heritabilities for clinical lipid traits are in the range of 0.30 to 0.70 (4Pilia G. Chen W-M. Scuteri A. Orrú M. Albai G. Dei M. Lai S. Usala G. Lai M. Loi P. et al.Heritability of cardiovascular and personality traits in 6,148 Sardinians.PLoS Genet. 2006; 2: e132Crossref PubMed Scopus (361) Google Scholar, 5Benyamin B. Sorensen T.I. Schousboe K. Fenger M. Visscher P.M. Kyvik K.O. Are there common genetic and environmental factors behind the endophenotypes associated with the metabolic syndrome?.Diabetologia. 2007; 50: 1880-1888Crossref PubMed Scopus (91) Google Scholar, 6Elder S.J. Lichtenstein A.H. Pittas A.G. Roberts S.B. Fuss P.J. Greenberg A.S. McCrory M.A. Bouchard Jr., T.J. Saltzman E. Neale M.C. Genetic and environmental influences on factors associated with cardiovascular disease and the metabolic syndrome.J. Lipid Res. 2009; 50: 1917-1926Abstract Full Text Full Text PDF PubMed Scopus (90) Google Scholar, 7Vattikuti S. Guo J. Chow C.C. Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits.PLoS Genet. 2012; 8: e1002637Crossref PubMed Scopus (152) Google Scholar, 8van Dongen J. Willemsen G. Chen W.M. de Geus E.J. Boomsma D.I. Heritability of metabolic syndrome traits in a large population-based sample.J. Lipid Res. 2013; 54: 2914-2923Abstract Full Text Full Text PDF PubMed Scopus (57) Google Scholar, 9Zaitlen N. Kraft P. Patterson N. Pasaniuc B. Bhatia G. Pollack S. Price A.L. Using extended genealogy to estimate components of heritability for 23 quantitative and dichotomous traits.PLoS Genet. 2013; 9: e1003520Crossref PubMed Scopus (220) Google Scholar), while blood pressure and obesity-related traits tend to vary between 0.20 and 0.50 (4Pilia G. Chen W-M. Scuteri A. Orrú M. Albai G. Dei M. Lai S. Usala G. Lai M. Loi P. et al.Heritability of cardiovascular and personality traits in 6,148 Sardinians.PLoS Genet. 2006; 2: e132Crossref PubMed Scopus (361) Google Scholar, 5Benyamin B. Sorensen T.I. Schousboe K. Fenger M. Visscher P.M. Kyvik K.O. Are there common genetic and environmental factors behind the endophenotypes associated with the metabolic syndrome?.Diabetologia. 2007; 50: 1880-1888Crossref PubMed Scopus (91) Google Scholar, 6Elder S.J. Lichtenstein A.H. Pittas A.G. Roberts S.B. Fuss P.J. Greenberg A.S. McCrory M.A. Bouchard Jr., T.J. Saltzman E. Neale M.C. Genetic and environmental influences on factors associated with cardiovascular disease and the metabolic syndrome.J. Lipid Res. 2009; 50: 1917-1926Abstract Full Text Full Text PDF PubMed Scopus (90) Google Scholar, 7Vattikuti S. Guo J. Chow C.C. Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits.PLoS Genet. 2012; 8: e1002637Crossref PubMed Scopus (152) Google Scholar, 8van Dongen J. Willemsen G. Chen W.M. de Geus E.J. Boomsma D.I. Heritability of metabolic syndrome traits in a large population-based sample.J. Lipid Res. 2013; 54: 2914-2923Abstract Full Text Full Text PDF PubMed Scopus (57) Google Scholar, 10van Rijn M.J. Schut A.F. Aulchenko Y.S. Deinum J. Sayed-Tabatabaei F.A. Yazdanpanah M. Isaacs A. Axenovich T.I. Zorkoltseva I.V. Zillikens M.C. et al.Heritability of blood pressure traits and the genetic contribution to blood pressure variance explained by four blood-pressure-related genes.J. Hypertens. 2007; 25: 565-570Crossref PubMed Scopus (72) Google Scholar). Clinical lipid measures such as total cholesterol, LDL-C, and HDL-C reflect the cholesterol component of the lipoprotein particles, which are complex mixtures of phospholipids, sphingolipids, free cholesterol, cholesteryl esters, and triglycerides (referred to as triacylglycerol (TG) species in the mass spectrometric measurements), together with a range of proteins (11Mundra P.A. Shaw J.E. Meikle P.J. Lipidomic analyses in epidemiology.Int. J. Epidemiol. 2016; 45: 1329-1338Crossref PubMed Scopus (16) Google Scholar). These lipid classes contain potentially thousands of individual molecular species that make up the human lipidome, which can now be measured using established low-cost high-throughput methods (12Weir J.M. Wong G. Barlow C.K. Greeve M.A. Kowalczyk A. Almasy L. Comuzzie A.G. Mahaney M.C. Jowett J.B. Shaw J. et al.Plasma lipid profiling in a large population-based cohort.J. Lipid Res. 2013; 54: 2898-2908Abstract Full Text Full Text PDF PubMed Scopus (238) Google Scholar). Lipids are transported through plasma as lipoproteins for exchange between the liver, intestine, and peripheral tissues. Their composition and abundance are likely to reflect underlying metabolic processes influenced by the environment, diet, and genetics (11Mundra P.A. Shaw J.E. Meikle P.J. Lipidomic analyses in epidemiology.Int. J. Epidemiol. 2016; 45: 1329-1338Crossref PubMed Scopus (16) Google Scholar). The individual species comprising the lipidome may represent novel predictors of CVD risk, particularly if measured in longitudinal cohort studies where causality may potentially be inferred (11Mundra P.A. Shaw J.E. Meikle P.J. Lipidomic analyses in epidemiology.Int. J. Epidemiol. 2016; 45: 1329-1338Crossref PubMed Scopus (16) Google Scholar, 13Alshehry Z.H. Mundra P.A. Barlow C.K. Mellette N.A. Wong G. McConville M.J. Simes J. Tonkin A.M. Sullivan D.R. Barnes E.H. et al.Plasma lipidomic profiles improve on traditional risk factors for the prediction of cardiovascular events in type 2 diabetes mellitus.Circulation. 2016; 134: 1637-1650Crossref PubMed Scopus (118) Google Scholar). Owing to their close proximity to an individual's metabolic state, genetic investigations into these lipid species may provide insight into CVD risk and prediction, above that already identified through the genetic analysis of the composite clinical lipid measures. This is particularly the case for lipid species that are genetically correlated with disease-related traits, as the search for pleotropic clues can be restricted to the more informative species (i.e., those that are heritable and genetically correlated). Associations between the circulating lipidome and CVD traits have provided insight into CVD etiology and identified novel biomarkers. Meikle et al. (14Meikle P.J. Wong G. Tsorotes D. Barlow C.K. Weir J.M. Christopher M.J. MacIntosh G.L. Goudey B. Stern L. Kowalczyk A. et al.Plasma lipidomic analysis of stable and unstable coronary artery disease.Arterioscler. Thromb. Vasc. Biol. 2011; 31: 2723-2732Crossref PubMed Scopus (196) Google Scholar) identified 13 lipid classes and 102 lipids associated with stable coronary artery disease (CAD) compared with healthy controls. In a more recent study, nine lipid classes/subclasses and 113 lipid species from the apoA fraction, and seven classes/subclasses and 113 lipid species from plasma were associated with unstable CAD (compared with stable CAD) (15Meikle P.J. Formosa M.F. Mellett N.A. Jayawardana K.S. Giles C. Bertovic D.A. Jennings G.L. Childs W. Reddy M. Carey A.L. et al.HDL phospholipids, but not cholesterol distinguish acute coronary syndrome from stable coronary artery disease.J. Am. Heart Assoc. 2019; 8: e011792Crossref PubMed Scopus (16) Google Scholar). In the Malmo Diet and Cancer study, incident cardiovascular events were marginally associated with lipid species belonging to the lysophosphatidylcholine (LPC), SM, and TG lipid classes (16Fernandez C. Sandin M. Sampaio J.L. Almgren P. Narkiewicz K. Hoffmann M. Hedner T. Wahlstrand B. Simons K. Shevchenko A. et al.Plasma lipid composition and risk of developing cardiovascular disease.PLoS One. 2013; 8: e71846Crossref PubMed Scopus (81) Google Scholar). Ganna et al. (17Ganna A. Salihovic S. Sundström J. Broeckling C.D. Hedman Å.K. Magnusson P.K.E. Pedersen N.L. Larsson A. Siegbahn A. Zilmer M. et al.Large-scale metabolomic profiling identifies novel biomarkers for incident coronary heart disease.ploS Genet. 2014; 10: e1004801Crossref PubMed Scopus (162) Google Scholar) found significant associations between incident coronary heart disease and 32 metabolites, five of which were also associated in an independent cohort. After adjustment for traditional CVD risk factors, the addition of lipid species to a base model predicting CVD events marginally improved for CVD events (C-statistic increased from 0.68 to 0.70) and CVD deaths (C-statistic increased from 0.74 to 0.76) (13Alshehry Z.H. Mundra P.A. Barlow C.K. Mellette N.A. Wong G. McConville M.J. Simes J. Tonkin A.M. Sullivan D.R. Barnes E.H. et al.Plasma lipidomic profiles improve on traditional risk factors for the prediction of cardiovascular events in type 2 diabetes mellitus.Circulation. 2016; 134: 1637-1650Crossref PubMed Scopus (118) Google Scholar). Similar results were seen in a study of 5,991 individuals from a population-based study, with the inclusion of seven lipid species in a traditional risk factor model improving the C-statistic by 0.025 and 0.054 for CVD events and CVD death, respectively (18Mundra P.A. Barlow C.K. Nestel P.J. Barnes E.H. Kirby A. Thompson P. Sullivan D.R. Alshehry Z.H. Mellett N.A. Huynh K. et al.Large-scale plasma lipidomic profiling identifies lipids that predict cardiovascular events in secondary prevention.JCI Insight. 2018; 3: e121326Crossref PubMed Scopus (52) Google Scholar). Numerous studies have estimated the heritability of the lipidome and its association and/or genetic correlation with CVD traits. In a study of Mexican Americans from the San Antonio Family Heart Study (19Bellis C. Kulkarni H. Mamtani M. Kent Jr., J.W. Wong G. Weir J.M. Barlow C.K. Diego V. Almeida M. Dyer T.D. et al.Human plasma lipidome is pleiotropically associated with cardiovascular risk factors and death.Circ Cardiovasc Genet. 2014; 7: 854-863Crossref PubMed Scopus (34) Google Scholar), all 319 lipid species were significantly heritable, with a median heritability of 0.37. This study also identified lipid species clustered associated with risk of cardiovascular death, and other CVD-related risk factors, such as obesity, type 2 diabetes, and higher triglycerides. In a more recent study of 2,181 individuals, Tabassum et al. (20Tabassum R. Rämö J.T. Ripatti P. Koskela J.T. Kurki M. Karjalainen J. Palta P. Hassan S. Nunez-Fontarnau J. Kiiskinen T.T.J. FinnGen Project Collaborators et al.Genetic architecture of human plasma lipidome and its link to cardiovascular disease.Nat. Commun. 2019; 10: 4329Crossref PubMed Scopus (36) Google Scholar) estimated SNP-based heritabilities of 141 lipid species ranging between 0.10 and 0.54. Strong genetic correlations were observed between TG and diacylglycerol (DG) lipid classes and the clinical lipid measure of triglycerides (average rg = 0.88). Most recently, Demirkan et al. (21Demirkan A. Pool R. Deelen J. Beekman M. Liu J. Harms A.C. Varhoost A. Verhoeven A. Amin N. van Dijk K.W. et al.Genome-wide association study of plasma lipids.bioRxiv. 2019; (10.1101/621334.)Google Scholar) examined the genetic correlation between 90 lipid species from TG, SM, phosphatidylcholine (PC), alkylphosphatidylcholine [PC(O)], LPC, phosphatidylethanolamine (PE), and alkylphosphatidylethanolamine [PE(O)] classes and identified genetic correlations between lipid species and clinical lipids (i.e., triglycerides, LDL-C, HDL-C), total body fat percentage, and BMI. These studies indicate that the human lipidome is heritable and highlight the genetic pleiotropy that exists between the plasma lipidome and CVD traits. The aim of this study was to estimate the heritability of the human lipidome and the genetic correlation between lipid classes and species with CVD traits using our expanded lipidomic profile (with more specific lipid species and new lipid classes) of the Busselton Family Heart Study. Participants (n = 4,492) studied were taken from the 1994/95 survey of the original participants of the long-running epidemiological study, the Busselton Health Study, for whom genome-wide SNP data, extensive phenotype data, and blood serum were available. The Busselton Health Study is a community-based study in Western Australia that includes both related and unrelated individuals (predominantly of European ancestry), and has been described in more detail elsewhere (22James A.L. Knuiman M.W. Divitini M.L. Hui J. Hunter M. Palmer L.J. Maier G. Musk A.W. Changes in the prevalence of asthma in adults since 1966: the Busselton Health Study.Eur. Respir. J. 2010; 35: 273-278Crossref PubMed Scopus (64) Google Scholar, 23Gregory A.T. Armstrong R.M. Grassi T.D. Gaut B. Van Der Weyden M.B. On our selection: Australian longitudinal research studies.Med. J. Aust. 2008; 189: 650-657Crossref PubMed Scopus (6) Google Scholar, 24Cadby G. Melton P.E. McCarthy N.S. Almeida M. Williams-Blangero S. Curran J.E. VandeBerg J.L. Hui J. Beilby J. Musk A.W. et al.Pleiotropy of cardiometabolic syndrome with obesity-related anthropometric traits determined using empirically derived kinships from the Busselton Health Study.Hum. Genet. 2018; 137: 45-53Crossref PubMed Scopus (4) Google Scholar). Informed consent was obtained from all participants and the 1994/95 health survey was approved by the University of Western Australia Human Research Ethics Committee (UWA HREC). The current study, the Busselton Family Heart Study, was approved by the UWA HREC. This study was conducted in accordance with the ethical principles of the Declaration of Helsinki. Targeted lipidomic profiling was performed in positive-ion mode using electrospray ionization-tandem mass spectrometry to quantify the major fatty acids of 596 lipid species from 33 lipid classes, from blood serum. Positive-ion mode only was selected to minimize the time required for analysis of each sample, while still providing good coverage of the lipidome (25Huynh K. Barlow C.K. Jayawardana K.S. Weir J.M. Mellett N.A. Cinel M. Magliano D.J. Shaw J.E. Drew B.G. Meikle P.J. High-throughput plasma lipidomics: detailed mapping of the associations with cardiometabolic risk factors.Cell Chem. Biol. 2019; 26: 71-84.e4Abstract Full Text Full Text PDF PubMed Scopus (90) Google Scholar). Profiling was performed at the Metabolomics Laboratory, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia. Serum lipids were isolated using a single phase butanol:methanol extraction (26Alshehry Z.H. Barlow C.K. Weir J.M. Zhou Y. McConville M.J. Meikle P.J. An efficient single phase method for the extraction of plasma lipids.Metabolites. 2015; 5: 389-403Crossref PubMed Scopus (74) Google Scholar) and quantified by liquid chromatography-tandem mass spectrometry as previously described (25Huynh K. Barlow C.K. Jayawardana K.S. Weir J.M. Mellett N.A. Cinel M. Magliano D.J. Shaw J.E. Drew B.G. Meikle P.J. High-throughput plasma lipidomics: detailed mapping of the associations with cardiometabolic risk factors.Cell Chem. Biol. 2019; 26: 71-84.e4Abstract Full Text Full Text PDF PubMed Scopus (90) Google Scholar). Briefly, serum samples (10 ul) were placed into a randomized order, with blank and pooled quality control samples placed every 20 and 10 serum samples, respectively. Serum aliquots were extracted in a single-phase extraction with the addition of 100 ul of butanol:methanol (1:1), containing a mix of 18 nonphysiological or stable isotope-labeled lipid standards between 10 and 10,000 pmol each. Lipid analysis was performed by liquid chromatography electrospray ionization-tandem mass spectrometry using an Agilent 1290 HPLC coupled to an Agilent 6490 triple quadrupole mass spectrometer. The ion source was operated in positive ionization mode, with conditions: gas temperature 150°C, gas flow 17 liters/min, nozzle pressure 20 psi, sheath gas temperature 200°C, sheath gas flow 10 liters/min, capillary voltage 3,500 V, nozzle voltage 1,000 V. Liquid chromatography was performed on a Zorbax Eclipse Plus C18, 1.8 um, 100 × 2.1 mm column (Agilent Technologies). Solvents consisted of water:acetonitrile:isopropanol containing 10 mM ammonium formate (solvent A, 50:30:20; solvent B, 1:9:90). The column was heated to 60°C and the autosampler regulated to 25°C. Lipid extracts (1 ul) were injected and separated under gradient conditions using a flow rate of 400 ul/min: 0 min, 10% B; 2.7 min, 45% B; 2.8 min, 53% B; 9 min, 65% B; 9.1 min, 89% B; 11 min, 92% B; 11.1 min, 100% B; 11.9 min, 100% B; 12.8 min, 10% B; 12.9 min, 10% B (flow rate 600 ul/min); 13.9 min, 10% B (flow rate 600 ul/min); 14 min, 10% B (flow rate 400 ul/min); held at 10% B and 400 ul/min until the next injection at 16.2 min. The first minute and last 3 min of each analytical run were diverted to waste. A total of 497 transitions, representing 596 lipid species, were measured using dynamic multiple reaction monitoring, where data were collected during a retention time window specific to each lipid species. Raw mass spectrometry data were analyzed using Mass Hunter Quant B08 (Agilent Technologies). Lipid concentrations were calculated by relating the area under the chromatographic peak for each lipid species to the corresponding internal standard. Correction factors were applied to adjust for differences in response factors, where these were known (25Huynh K. Barlow C.K. Jayawardana K.S. Weir J.M. Mellett N.A. Cinel M. Magliano D.J. Shaw J.E. Drew B.G. Meikle P.J. High-throughput plasma lipidomics: detailed mapping of the associations with cardiometabolic risk factors.Cell Chem. Biol. 2019; 26: 71-84.e4Abstract Full Text Full Text PDF PubMed Scopus (90) Google Scholar). Details of the Busselton Health Study data collection have been published previously (27Knuiman M.W. Hung J. Divitini M.L. Davis T.M. Beilby J.P. Utility of the metabolic syndrome and its components in the prediction of incident cardiovascular disease: a prospective cohort study.Eur. J. Cardiovasc. Prev. Rehabil. 2009; 16: 235-241Crossref PubMed Scopus (39) Google Scholar). For this study, we examined eight CVD phenotypic variables: HDL-C, LDL-C, triglycerides, total cholesterol, SBP, DBP, BMI, and waist-hip ratio (WHR). Serum cholesterol and triglycerides were calculated by standard enzymatic methods on a Hitachi 747 (Roche Diagnostics, Sydney, Australia) from fasting blood collected in 1994/95. HDL-C was determined on a serum supernatant after polyethylene glycol precipitation using an enzymatic cholesterol assay and LDL-C was estimated using the Friedewald formula (28Friedewald W.T. Levy R.I. Fredrickson D.S. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge.Clin. Chem. 1972; 18: 499-502Crossref PubMed Scopus (61) Google Scholar). Five minute resting SBP and DBP were used. Height and weight (used to calculate BMI) were collected from participants at the time of interview (1994/95). WHR was calculated as waist circumference (centimeters) / hip circumference (centimeters). Use of antihypertensive and lipid-lowering medications was collected at interview (1994/95). Genotyping was performed on the Illumina Human 610K Quad-Bead Chip (Illumina Inc., San Diego, CA) at the Centre National de Genotypage in Paris, France (n = 1,468), and on the Illumina 660 W Quad Array Bead Chip (Illumina Inc.) at the PathWest Laboratory Medicine WA (Nedlands, Western Australia, Australia) (n = 3,428). Complete linkage clustering based on pairwise identity by state distance in PLINK (29Purcell S. Neale B. Todd-Brown K. Thomas L. Ferreira M.A.R. Bender D. Maller J. Sklar P. de Bakker P.I.W. Daly M.J. et al.PLINK: a tool set for whole-genome association and population-based linkage analyses.Am. J. Hum. Genet. 2007; 81: 559-575Abstract Full Text Full Text PDF PubMed Scopus (17633) Google Scholar) showed no batch effects, therefore the batches were merged. Standard genotype data quality control was performed [described in further detail elsewhere (24Cadby G. Melton P.E. McCarthy N.S. Almeida M. Williams-Blangero S. Curran J.E. VandeBerg J.L. Hui J. Beilby J. Musk A.W. et al.Pleiotropy of cardiometabolic syndrome with obesity-related anthropometric traits determined using empirically derived kinships from the Busselton Health Study.Hum. Genet. 2018; 137: 45-53Crossref PubMed Scopus (4) Google Scholar)]. Briefly, we excluded SNPs with: call rates <95%, minor allele count <10, and deviations from Hardy-Weinberg equilibrium (P < 5.0 × 10−4). Individuals were excluded if: >3% of SNP data were missing (n = 11), reported sex did not match genotyped sex (n = 48), duplicates (n = 123), missing phenotype data (n = 11), or >5 standard deviations above/below mean heterozygosity (n = 28). Individuals with non-European ancestry (n = 4) were also excluded. We first used the general linear mixed effects model incorporated in the Sequential Oligogenic Linkage Analysis Routines (SOLAR) (30Almasy L. Blangero J. Multipoint quantitative-trait linkage analysis in general pedigrees.Am. J. Hum. Genet. 1998; 62: 1198-1211Abstract Full Text Full Text PDF PubMed Scopus (2533) Google Scholar) to estimate the narrow-sense heritabilities of lipid classes (n = 33), lipid species (n = 596), and eight CVD traits: HDL-C, LDL-C, triglycerides, total cholesterol, SBP, DBP, BMI, and WHR. SOLAR uses a variance-component method to partition observed covariance between individuals into genetic and environmental components. Heritability is defined as the variance in the trait due to additive genetic effects divided by the sum of the additive genetic effects and the random (unmeasured) environmental effects. The null hypothesis of no heritability (h2 = 0) was tested by comparing the log likelihood for the full model [with the genetic relatedness matrix (GRM)] and the reduced model (without the GRM), using likelihood ratio tests. Twice the difference in log-likelihoods of these models was distributed as a χ2 random variable with 1 degree of freedom. Genetic correlations between lipid classes/species and eight CVD traits were calculated in SOLAR. Lipid classes were defined as the sum of the lipids within each class (i.e., total lipid abundance for each class). Genetic correlations were estimated using a variance components model to partition the phenotypic correlation between the traits into proportion of variability due to shared genetic effects (ρg) and the proportion of variability due to shared environmental effects. The null hypothesis of no genetic correlation (rg = 0) was tested by comparing the log likelihood for the full model (with the GRM) and the reduced model (without the GRM), using likelihood ratio tests. All heritability and genetic correlation analyses included a GRM, to exploit both known and unknown relatedness in the sample. We estimated empirical kinship probabilities between pairs of individuals from all genome-wide SNP data using Linkage Disequilibrium Adjusted Kinships (LDAK) software (31Speed D. Hemani G. Johnson M.R. Balding D.J. Improved heritability estimation from genome-wide SNPs.Am. J. Hum. Genet. 2012; 91: 1011-1021Abstract Full Text Full Text PDF PubMed Scopus (346) Google Scholar), as described previously (24Cadby G. Melton P.E. McCarthy N.S. Almeida M. Williams-Blangero S. Curran J.E. VandeBerg J.L. Hui J. Beilby J. Musk A.W. et al.Pleiotropy of cardiometabolic syndrome with obesity-related anthropometric traits determined using empirically derived kinships from the Busselton Health Study.Hum. Genet. 2018; 137: 45-53Crossref PubMed Scopus (4) Google Scholar), to form the GRM. Any value of kinship in the GRM less than 0.05 was set to zero to minimize potential bias from using both closely and distantly related individuals. Using this method, heritability estimates derived from SNP data have been shown to be similar to those obtained from using identity-by-descent measures from pedigrees with known pedigree structures (9Zaitlen N. Kraft P. Patterson N. Pasaniuc B. Bhatia G. Pollack S. Price A.L. Using extended genealogy to estimate components of heritability for 23 quantitative and dichotomous traits.PLoS Genet. 2013; 9: e1003520Crossref PubMed Scopus (220) Google Scholar). Rank-based inverse normal transformed residuals were used in all analyses. All analyses included adjustments for age, sex, age2, and their interactions, age × sex and age2 × sex. Adjustment for age and sex were included in heritability and genetic correlation analyses to estimate the additive genetic effects of lipid classes/species and CVD traits after accounting for these covariates. In addition, interaction terms were included as the relationship between outcomes (lipid classes/species and CVD traits) and age was different between men and women (age × sex interaction). We also identified that the relationship between outcomes and age was not linear, hence the inclusion of age2 and the age2 × sex interaction. In our heritability and genetic correlation analyses, these interactions consistently showed P-values <0.05. For individuals taking antihypertensive medications (n = 507), their SBP and DBP measures were increased by 10 mmHg and 5 mmHg, respectively. In addition, lipid measures were corrected by the use of lipid-lowering medications, by matching individuals taking lipid-lowering medication (n = 108) and individuals not taking medication on age, sex, and BMI, and calculating a multi" @default.
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• W3006663297 title "Heritability of 596 lipid species and genetic correlation with cardiovascular traits in the Busselton Family Heart Study" @default.
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